IEEE

A Mixture-Gas Multisensor Interface With On-Chip Classification and On-Edge Regression

Abstract: This article presents a mixture-gas detectable edge-computing device with two-step on-sensor classification and regression capabilities. The mixture-gas classification is achieved through a ...
SciELO

Obesity classification: a comparative study of machine learning models excluding weight and height data

OBJECTIVE: Obesity is a global health problem. The aim is to analyze the effectiveness of machine learning models in predicting obesity classes and to determine which model performs best in obesity ...
IEEE

A Comprehensive Machine Learning Approach for Wild Fire Detection and Classification Using Squeezenet and Ridge Regularized Logistic Regression

Abstract: Wild fire is a serious environmental and socioeconomic menace and therefore any effort aimed at the early and accurate detection of wild fire has to be very useful. This paper proposes a ...
GitHub

lasso-regression

Python machine learning applications in image processing, recommender system, matrix completion, netflix problem and algorithm implementations including Co-clustering, Funk SVD, SVD++, Non-negative ...
Frontiers

A novel dynamic nomogram based on contrast-enhanced computed tomography radiomics for prediction of glypican-3-positive hepatocellular carcinoma

Background: The 5-year overall survival of hepatocellular carcinoma (HCC) is still poor. Since glypican-3 (GPC3) is highly expressed in most HCC but not in healthy or non-malignant livers, it may ...
GitHub

Multi-Niche Misinformation Detection

A modular text classification system that detects misinformation across multiple domains. Each niche has its own dataset, labeling rules, and baseline models (TF-IDF + Logistic Regression / Linear SVM ...